The Fariborz Maseeh Department of Mathematics and Statistics and
The Maseeh Mathematics and Statistics Colloquium Series*
Simulating Dependent Discrete Data
by Lisa Madsen, Ph.D., Department of Statistics, Oregon State University
Friday, January 17th, 2014 at 3:15pm
Neuberger Hall room 454, Portland State University
(Refreshments served at 3:00 in presentation room)
This event is free and open to the public.
Statisticians use simulated data to assess and compare the performance of statistical procedures. Therefore, the ability to simulate realistic data is an important tool. I will present a method to simulate count-valued dependent random variables that mimic observed data sets. The method simulates a correlated normal random vector, then transforms to the desired marginal distributions. The difficulty is in establishing the normal correlations that yield the desired dependence and even in characterizing the desired dependence. I focus on two measures of dependence, Pearson's produce-moment correlation and Spearman's rank correlation. I will show how to determine the normal correlation matrix that will lead to any specified feasible Pearson or Spearman correlation matrix. To illustrate the method, I'll simulate data to mimic two real data sets, one longitudinal and the other ecological.
Dr. Madsen’s current research interests include: dependent discrete data, abundance and occupancy models, spatial statistics, statistical computing and simulation, environmental statistics.
* Sponsored by the Maseeh Mathematics and Statistics Colloquium Series Fund and the Fariborz Maseeh Department of Mathematics & Statistics, PSU.